【课程代码】用NumPy和Pandas做数据分析实战.zip

# -*- coding: utf-8 -*- """ 明确任务：绘制不同用户季度平均骑行时间的分组柱状图 """ import os import numpy as np import matplotlib.pyplot as plt from matplotlib.font_manager import FontProperties # 解决matplotlib中文显示问题，仅适用mac系统 def get_chinese_font(): return FontProperties(fanme='/System/Library/Fonts/PingFang.ttc') data_path = './data/bikeshare/' #数据源和迷你数据源均和上一节课相同，所以不重复放到这节课的文件夹里了 data_filenames = ['2017-q1_trip_history_data.csv', '2017-q2_trip_history_data.csv', '2017-q3_trip_history_data.csv', '2017-q4_trip_history_data.csv'] # 结果保存路径 output_path = './output' if not os.path.exists(output_path): os.makedirs(output_path) def collect_process_analyze_data(): """ Step 1+2+3: 数据获取，数据处理，数据分析 """ member_mean_duration_list = [] casual_mean_duration_list = [] for data_filename in data_filenames: data_file = os.path.join(data_path, data_filename) data_arr = np.loadtxt(data_file, delimiter=',', dtype='str', skiprows=1) # 去掉双引号 # 骑行时间 duration_col = np.core.defchararray.replace(data_arr[:, 0], '"', '') duration_col = duration_col.reshape(-1, 1) # 用户类型 member_type_col = np.core.defchararray.replace(data_arr[:, -1], '"', '') member_type_col = member_type_col.reshape(-1, 1) duration_member_type_arr = np.concatenate([duration_col, member_type_col], axis=1) # 会员平均骑行时间 member_arr = duration_member_type_arr[duration_member_type_arr[:, 1] == 'Member'] member_mean_duration = np.mean(member_arr[:, 0].astype('float') / 1000 / 60) member_mean_duration_list.append(member_mean_duration) # 非会员平均骑行时间 causal_arr = duration_member_type_arr[duration_member_type_arr[:, 1] == 'Casual'] casual_mean_duration = np.mean(causal_arr[:, 0].astype('float') / 1000 / 60) casual_mean_duration_list.append(casual_mean_duration) return member_mean_duration_list, casual_mean_duration_list def save_and_show_results(member_mean_duration_list, casual_mean_duration_list): """ Step 4: 结果展示 """ bar_locs = np.arange(4) bar_width = 0.35 # 柱子宽度 xtick_labels = ['第{}季度'.format(i + 1) for i in range(4)] # xtick_labels = [] # for i in range(4): # xtick_labels.append('第{}季度'.format(i + 1)) plt.figure() plt.bar(bar_locs, member_mean_duration_list, width=bar_width, color='g', alpha=0.7, label='会员') plt.bar(bar_locs + bar_width, casual_mean_duration_list, width=bar_width, color='r', alpha=0.7, label='非会员') plt.xticks(bar_locs + bar_width / 2, xtick_labels, rotation=45, fontproperties=get_chinese_font()) plt.ylabel('平均骑行时间（单位：分钟）', fontproperties=get_chinese_font()) plt.title('柱状图', fontproperties=get_chinese_font()) plt.legend(loc='best', prop=get_chinese_font()) plt.tight_layout() plt.savefig(os.path.join(output_path, 'group_bar_chart.png')) plt.show() def main(): """ 主函数 """ # Step 1 + 2 + 3: 数据获取，数据处理，数据分析 member_mean_duration_list, casual_mean_duration_list = collect_process_analyze_data() save_and_show_results(member_mean_duration_list, casual_mean_duration_list) if __name__ == '__main__': main()